Math Vocabulary

2. of error: The difference between the point estimate and the true parameter value will be less than the margin of error in C% of all samples, where C is the confidence level
4. estimate: Specific value of a point estimator from a sample.
6. The probability that a test will reject H0 at a chosen significance level α when a specified alternative value of the parameter is true.
9. Interpret your interval in the context of the problem.
10. statistic: Calculation that measures how far a sample statistic diverges from what we would expect if the null hypothesis H0 were true, in standardized units.
11. level: Fixed value α that we use as a cutoff for deciding whether an observed result is too unlikely to happen by chance alone when the null hypothesis is true. The significance level gives the probability of a Type I error.
12. II error occurs if we fail to reject H0 when Ha is true. In other words, the data don’t give convincing evidence for Ha, even though the alternative hypothesis is correct.
14. error: When the standard deviation of a statistic is estimated from data, the result is the standard error of the statistic.
15. hypothesis: Claim we weight evidence against in a significance test. Often the null hypothesis is a statement of “no difference.”
16. of freedom: n-1

1. to reject: If the observed result is not very unlikely to occur when the null hypothesis is true, we should fail to reject H0 and say that we do not have convincing evidence for Ha.
3. The data should come from a well-designed random sample or randomized experiment.
5. Counts: The method that we use to construct a confidence interval for p depends on the fact that the sampling distribution of p-hat is approximately Normal.
7. hypothesis: The claim that we are trying to find evidence for in a significance test.
8. value: Multiplier that makes the interval wide enough to have the stated capture rate. The critical value depends on both the confidence level C and the sampling distribution of the statistic.
10. Percent Rule: When taking an SRS of size n from a population of size N, check that 10n is less than or equal to N
13. The probability, computed assuming H0 is true, that the statistic would take a value as extreme as or more extreme than the one actually observed, in the direction specified by Ha. The smaller the P-value, the stronger the evidence against H0 and in favor of Ha provided by the data.
16. If the conditions are met, perform calculations.